Towards the use of dynamic growing seasons in a chemical transport model
Chemical transport models (CTMs), used for the prediction of, for example, nitrogen deposition or air quality changes, require estimates of the growing season of plants for a number of reasons. Typically, the growing seasons are defined in a very simplified way in CTMs, using fixed dates or simple functions. In order to explore the importance of more realistic growing season estimates, we have developed a new and simple method (the T5 method) for calculating the start of the growing season (SGS) of birch (which we use as a surrogate for deciduous trees), suitable for use in CTMs and other modelling systems. We developed the T5 method from observations, and here we compare with these and other methodologies, and show that with just two parameters T5 captures well the spatial variation in SGS across Europe.
We use the EMEP MSC-W chemical transport model to illustrate the importance of improved SGS estimates for ozone and two metrics associated with ozone damage to vegetation. This study shows that although inclusion of more realistic growing seasons has only small effects on annual average concentrations of pollutants such as ozone, the metrics associated with vegetation risk from ozone are significantly affected.
This work demonstrates a strong need to include more realistic treatments of growing seasons in CTMs. The method used here could also be suitable for other types of models that require information on vegetation cover, such as meteorological and regional climate models. In future work, the T5 and other methods will be further evaluated for other forest species, as well as for agricultural and grassland land covers, which are important for emissions and deposition of reactive nitrogen compounds.